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Features description – Knomee

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Posted by knomee on

Do whatever you want with your data

KnomeeOpenFormat

A key principle from the quantified self movement is that you should use tools that let you do whatever you want with your data, that is, that do not keep the data locked in some proprietary format.

Knomee stores two types of data on your iPhone:

  • measure data, that you generate each time you record a value from one of your quest.
  • quest meta-data, that describes how the measure data should be interpreted.

Measure data can be exported and imported through CSV files, as shown on the illustration.

  1. to export your data, you press the export button on the "chart view" (small rectangle with a outward arrow), and Knomee produces an email addressed to you with a CSV (comma separated values) file of all the measures from this quest. You can upload them in Excel or any tool of your choice.
    The format is:  date, longitude, latitude, measure target value, measuer first factor value, second factor value, third factor value.
  2. to import your data, you open the measure list interface (second screenshot on the illustration) and you click the import button (small rectangle with an inward arrow). This will open a text zone where you can paste any CSV file that you have copied from your phone. Using these two steps is a way to perform back-up & restore.

Meta-data can be exported and imported as JSON files.  The JSON format is a self-evident description of your quests, its attributes and its trackers.

  1. to export a quest, you open the edit interface and click on the export button. This will generate an email to yourself, with the JSON description of your quest. Remember our promise to use only email as a tool to move data out from the application so that you may control this flow better.
  2. to import a quest, you open the quest list interface (as if you were to select a quest), and you will seen the import button (same, a small rectangle with an inward arrow). This will open a text zone where you can paste the quest description.

What you need to remember is that your data belongs to you (we cannot see it at Knomee) and that it is not stuck in your app, you can get it back whenever you want.

Knomee 2.0 will make sharing quest descriptions easier since we will create an open GitHub with all the Quest Library descriptions. Anyone will be able to add to this list of quests.

 

 

Posted by knomee on

Design your own self-tracker for 2019 !

SelfTrackingAdvertising

Happy new year from the Knomee application team !

January first is traditionally the time for "New Year resolutions" ... that do not survive a few weeks most of the time. Self-tracking can help : science has shown repeatedly that tracking your goals and your habits develop both self-awareness and motivation.

Knomee is not just a tracking app, it is a generator for customised tracker. Using Knomee you can create in less than 10 minutes your very own tracker.

The picture above illustrates how you can use Knomee to track virtually everything. Four examples are shown:

  • The first one is a "business life / performance" case where you want to see how to improve the engagement in your meetings. You assess the performance (i.e. engagement here) of each meeting that you attend, and you also track three factors : the number of attendees, the duration of the meeting and the presence of a meeting agenda.
  • The second example is self-tracking applied to improving your family chocolate cake recipe. You track how good your cake tested based on which kind of chocolate you used, how much sugar you used and how long the cake stayed in the oven. Obviously, as soon as you have found the best parameters with those three factors, you will move to other such as the amount of butter or the oven temperature.
  • You can use Knomee to monitor your performance with any kind of activity, since you are free to use your own scales with your own words (labels). Here we show a "Ultimate game tracker" where you also track your heart rate and weather factors such as wind and visibility.
  • The last example shows how personal self-tracking can be. Here the Knomee user is suffering from bladder discomfort when urinating, and trying to see if the number of drinks (especially coffees) and the current stress level have an impact and could be used to reduce the discomfort.

These four examples have nothing to do with New Year resolutions ... because each of these resolution (quit smoking, loose weight, play more with your kids, read a book each month, ...) is personal and we thought that showing you examples of resolutions might downplay your motivation.

It is time to act, and it is your job : define your new lifestyle tracker and use Knomee to get some insights about yourself.

When you start Knomee, it comes with three pre-defined quests, to help you get familiar with the app (mood, energy and sleep). Most often, we hear as first feedback : "Knomee is not for me, I do not care about these things. I don't want to track my mood and my sleep/energy patterns are fine". This is not what Knomee is about ! Knomee is about tracking what matters to you. Thus you should quickly forget about the pre-defined quests and build your own.

If you should remember one thing :

Knomee is not a self-tracking app,
it is a tool to help you define your personalised tracker.

 

 

Posted by knomee on

Scoring Quests with Knomee

 

Knomee assign a score (from zero to 100%) to each quest, that is displayed on the main screen in the upper right corner. If you click on this number, you access the quest score view which is illustrated with the image above. Here you see a quest with a score 68%. To follow-up on the previous post, this is a quest whose target is “fitness” (that is measured using labels who are unique to the user of this quest), while the three factors are respectively the amount of ingested fat, ingested cereals and the rest heart rate as measured by the Apple Watch.

 

This score is made of three parts :

  • The quantity of data : a third of the score tells you  if you have accumulated enough data to get significant insights. Depending on your data, Knomee will wait until you have between 30 and 60 measures to give you a high score on this part. In the example that is show in the picture above, you can see in the green box that this first component is 100% (there is enough data, as told by the comment)
  • The insight score : this tells you if Knomee has found interesting insights using the three factors, or the time, day and location of the measure. If this sub-score is high, you will see that the relevant factors are coloured. In this case, “fat” and “cereal” are positively correlated, so they are coloured as green. The “chart view” is where you will get more details, but if you click on one of the factors, you will get a short insight summary as a forecast. In this example, the strength of the insights is not very strong so the sub-score is 25%.
  • The forecast score : this says if Knomee is able to forecast your successive measures well. Recall that whenever you enter a new measure, Knomee pre-position the sliders to its “guessed” value. This is mostly offered as a way to make the app faster and more playful, but Knomee keep the score on its forecasting capability. In this example, Knomee is on average 10% away from the actual value, which translates into a good third subscore of 77%. A good forecasting score is a sign of Granger-causality.

 

At first you will simply look at the score on the main user screen (the measure capture screen is the home screen), but after a while you will probably venture to this quest score screen to understand your quest score better. You can see that the rest of the screen displays a description of your quests, with colors to attract your attention on the relevant factors.

What does my score tell me?

  • A score below 50% says that either your quest is too young … or that it is not very significant. There may be many explanations, but most often it means that your causal diagram hypothesis is false. Put more bluntly, it means that your factors do not seem to have much influence on your target. As said repeatedly, this is a critical feature: Knomee helps you distinguish between your “hunches” and “data-supported causation schemes”. As it turns out, we are often “fooled by randomness”.
  • A score over 70% says the opposite: your “causal hypothesis”, i.e., your quest, is definitely interesting. By navigating through the various screens, you are likely to find interesting insights. If you have allowed Knomee to send you notifications, you will receive one of these insights daily.
  • A score in between means that your quest is interesting but there are probably many other factors influencing your “target”.

Knomee has no ambition to know you or to understand you. It is your job to understand yourself better through this self-tracking and these insights. The ambition of Knomee is to help you craft interesting self-tracking quests. The score is a great tool to help you during this journey. You should try quests and drop those whose score stay low. You should play with factors to see if some new factor improves or decreases your score. There are three stages of using Knomee:

  • At first, play with the default quests to get familiar with the app. Although we tried to select three quests with a broad range of interest, you are likely to get bored quickly or to say “this is not for me”. Remember that there is a “quest library” so you can substitute many other quests to start this first learning stage.
  • Knomee starts to be interesting when you define your own quest. We have tried to make this as simple as possible, and we shall continue to work on our design. Knomee is not “another self-tracking app”, it is “your own tracking app”. It takes five minutes to define a new quest, and then you can enjoy a tool that is unique to you. However, our experience suggests that you need to play with the existing quests (stage 1) before moving to stage 2.
  • There is only a finite amount of self-knowledge that your will extract from a given quest. After a delay that varies from a few weeks to a few months, you will be done with that quest. There are two ways to keep using Knomee : try a new quest, randomly, once in while … or continuously optimize your quest by changing the factors, the scales, or the data sources (switching from declarative values – when you input your data- to automatic values – when the value is read from a connected device through HealthKit).

Once you reach this third quest, you should consider sharing your quest with others. The screen shown above has an “envelope” button that allows you to share a recommendation through email. In the future we plan to make quest sharing simpler and more seamless.

 

 

Posted by knomee on

What is a Quest and why does Knomee use quests ?

Quests are central to the Knomee experience. On the negative side, they make Knomee a self-tracking app with a steeper learning curve, that requires a little bit more time and effort, compared, for example, with one of the activity or mood tracker that one may find on the App Store. On the positive side, quests give more sense to tracking, they make the tracking experience more fulfilling and they help Knomee give you more meaningful feedback about yourself. A quest is a group of things that you want to track, each of them is called a tracker. Trackers are defined by one thing (weight, sleep, activity, mood, etc.) that you track, either by entering the value (using the sliders in Knomee’s interface) or by importing the value from “HealthKit”, the Apple service on your iPhone that collects all data from your connected devices (wristband, watch, scale, sleep monitor, etc.) or your iPhone itself.

A quest is what is called a “causal diagram” (albeit a simple one) in the scientific world. This means that a quest represents a causal hypothesis that you make, about yourself. A quest has one target and one to three factors. When defining a quest, you tell Knomee that up to three factors (say, the time you go to bed, the amount of steps that you walked, and the richness of the dinner that you had) have a causal influence on something that you care about, the target tracker (in this example, it could be the number of hours that you slept).

Self-tracking is good for you but boring. This is not an opinion, this is a scientific fact. It is proven that self-tracking helps you both to know yourself better and to help you change your behaviour towards a goal. It is also proven than most people stop self-tracking quickly, from a few days to a few weeks. Knomee was created to tackle this challenge, and it is a hard one.

The only thing that makes this self-tracking worthwhile is learning about yourself. This is why we selected “self-tracking with sense” as our motto. We came up with the quest idea for two reasons. First, a “quest” is “indeed a quest to know yourself better” and to see if your “causal hypothesis” happens to work. In many cases, using Knomee is a way to see if doing some particular effort is “worth it”.  Second, a causal diagram is a powerful tool to orient the machine learning and statistical analysis. It makes the problem of “making sense from your data” easier and helps us keep everything on your phone (hence our guarantee of full privacy).

Quests don’t last: you formulate a hypothesis, you learn (or you don’t) from it and you move to other things. We have made it easy to add and drop quests to Knomee. Our usage statistics show that this is not properly understood yet. Many users start with the pre-defined quests and never venture to create their own. This is a shame since it is unlikely that those pre-defined causal diagrams apply to you.

Quests are meant to be shared: the future of Knomee is to make it easier to share successful quests with others (sharing the model, the causal diagram, not your data). In a reciprocate way, it would be nice to be able to look at quests that have been successful for people who have the same “target” goals. For instance, although everyone is different, it would be nice to have access to a collection of successful quests from people who tried to improve the quality of their sleep.  Currently, sharing is possible but cumbersome: you send the model/quest description to a friend through email … and she/he may import it.  The quest library is another way to benefit from quest sharing but this feature is still in an infancy stage.

You may wonder why  no other tracking app is using quests. This is because we take our mission “self-tracking with sense” seriously. It is clear that it is hard to make sense with one single tracking dimension. You know this already if you are using a tracking app or if you are looking at your health app on your iPhone. At first seeing all this data and this nicely shaped charts is exciting, but you get rapidly bored because there is not much value there. The chronology (looking for weekly, daily and hourly patterns) is the most interesting part, but only a few apps do a decent job at it. If you “self-track” regularly, you will notice that the interesting questions arise from the combination of factors. There are a few Knomee competitors that upload all data in the cloud to search for any interesting combination or pattern. We already said that using quests (simple causal diagrams) makes the analysis simpler and suitable for a “device-only” solution (everything on your phone) but there is another reason for using quests. You are in charge, you know better than anyone what questions are interesting for you.

Posted by knomee on

Knomee “sense-making” algorithms just improved !

A new version of Knomee, 1.9, has been made available on the Apple AppStore just before Thanksgiving. It has been almost six months since the previous (1.8) release, we took the complete summer to re-calibrate the insights and forecasting algorithms. After a year in existence, we have accumulated enough experience to improve the robustness and the relevance of Knomee algorithms. Insights, scores and data visualization explanation will be more relevant and robust in the future.

We did not only improve “the engine under the hood”, we have also added a number of significant improvements to make it easier to use Knomee:

  • We have added quests categories : sleep, mood, food, health and activity. It makes navigating and selecting new quests easier. You will recognize the quest category with a small icon that is displayed next to the quest name in your quest list or library. Sleep tracking is on the rise since the amount of evidence that sleep is our #1 tool to improve our well being keeps piling up. There are many apps and devices to help you track your sleep (we like AutoSleep) but there is only Knomee to help you understand why you are getting good or bad sleep numbers.
  • The user interface for quest score has been simplified, and we dropped the “ken score” name that was confusing to most of you. The quest score tells you how “interesting” and “robust” your quest is. A score below 50% says that either you do not have enough data, or that your quest is not insightful, that is, the factors that you are tracking do not seem to play a significant quest towards your goal. Remember that Knomee’s number-one value is to help you find out if there is a relationship between differents aspects of your life that you are tracking. Most often, there is none ! We are “fooled by randomness” to quote Nassim Taleb. A low quest score tells you that you may be looking for sense where there is none.
  • Navigation between the different user interfaces leverages iOS transitions better. The user manual with its tip section has been improved, it should be easier to learn about Knomee while using it.
  • The use of coloring for feedback has both been extended (when you enter a new measure) and improved. The first part is that Knomee signals you whenever you enter a new measure whether you are close or far from the target values that you have set. Knomee uses the same color scheme to indicate “good” to “worse” values, and remember that you can change it in the options. If you are new to Knomee, the “blue” color setup is the simplest to use because of its vivid colors : red is bad and green is good. The second part is what make Knomee different from other tracker apps: as soon as you have enough data, Knomee uses red/green colors to tell you which factor “help” or “play against” your target. You get this coloring in the “Chart user interface” (click on the “eye button”) and with the quest score interface.
  • Insight generation has been improved both in wording and relevance. When you have enough data, and if you have enabled notifications, Knomee will send you insights daily in the form of short notification messages. All this information is available at any time in the “chart” user interface.

 

 

Knomee uses a family of algorithms for analyzing and forecasting self-tracking time series. Stay posted on our web site since we plan to share more about this in 2019. When you use Knomee most of this is implicit : Forecasting is used to animate the sliders and make your self-tracking more efficient, trend analysis is embedded into the mountain icons (the mountain shape tells you about the distance to the target and the weather tells you about the trend), tracker scores are transformed into colors and insights.

When used right, Knomee has the potential to change your life and help you to improve your health significantly - it has happened to this author. This has nothing to do with the technology that is embedded in the Knomee mobile application but everything to do with the fact that behavior change can indeed improve your health and your wellbeing. One of key challenges that the Knomee team faces is to keep simplifying the Knomee user experience so that everyone can enjoy the benefits of a mobile-computer-aided self-tracking. This is why we constantly ask for feedbacks from you, our early-users community.

Posted by knomee on

Todards the best quantified self quest editor

QuestEditor

We are proud to announce that Knomee 1.8 was released last week on the Apple Store. In addition to a number of minor improvements and bug fixes, this release brings the following new features:

  • each quest can now receive its own « collection frequency » which is, how often do you intend to self-track for this quest. In the quest list, Knomee uses color to tell you quests that are waiting for your measures. It used to be defined by your options but with the same frequency for all quests. Now you can say that some quests require frequent tracking (every 4 hours or every 6 hours) while some other are tracked once a day or once a week. Together with the option to temporarily ignore a quest and then restore it later (which was introduced in 1.7), this makes Knomee a great mobile laboratory to play and experiment with quests. There is no sustainable self-tracking without a goal, experts tell us ... and crafting the right quest is the foundation of successful self-tracking.
  • Knomee now offers four different color schemes, to emphasise the personalisation. Your self-tracking app is like your personal diary, it should be unique and feel like it. Let us know which colors you like/dislike and we may add a few other combinations. Although coloring may sound downright futile, self-quantified brings tremendous value to one’s life once the habit is formed. Our toughest battle with Knomee is making your diary moment as pleasant and as quick as possible so that you may collect enough data to start seeing these benefits.
  • Knomee leverages four features of your smartphone : notifications, cloud storage (quest definitions, not data !), geolocation and HealthKit data. You can see at a glance on the home page which options you have allowed (the four associated icons are grayed if the feature is disabled). With release 1.8, if you click on one of these four icons, Knomee will remind you what it is using.
  • Knomee 1.8 brings better Data Visualisation (Dataviz in our jargon). Knomee 1.9 will bring even better insight algorithms - the current version h1s improved both the textual feedback as well as the displays (the charts). Hourly and Daily analysis are now much easier to read (and more precise). The geolocation map analysis is now working pretty well and will tell you if location matters to your quest and where you seem to fare better or worse.
  • Not everyone is a quantified self geek and most of you may not wish to look at the dataviz screens. This is why Knomee has a « smart notification engine » which looks at these charts for you and send you a notification once in a while about some insight of interest for you.  Knomee 1.8 has considerably increased the quality of the insights produced from data analysis ... hence the frequency has increased, once you have achieved the adequate maturity level with Knomee.

The journey towards generating smart insights from your data is a long one. This summer will be spent on implementing a new generation of machine learning algorithms. You may expect Knomee 1.9 this autumn with even better analytical skills. Still, we hope that you will enjoy the improved usability of Knomee with this 1.8 release.

The Knomee team.

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Posted by knomee on

Knomee Sense-making Algorithm is Grown from your Data

In his famous 1995 book “Out of Control”, Kevin Kelly wrote that smart systems should be “grown, not designed”. He meant that intelligent behavior should emerge from collected data and experience and not engineered in a top down way.

This is exactly how Knomee “smarts” (as in “self-tracking with sense”) have been developed: the pattern-detection algorithm is grown not designed. Knomee holds an “algorithm factory” in your smartphone, that “grows” a specific algorithm from your data, which is unique by construction.

 

(1) Knomee uses AI for Forecast and Statistical Validation

Knomee uses a number of techniques to provide insights and feedback. Most of it is classical statistical lore, but Knomee uses artificial intelligence to craft an algorithm that tries to « understand » your data, which means here to detect a collection of relevant patterns. This algorithm then serves two purposes. First it is use as a « forecasting » oracle. This is useful since it means that when you open Knomee the tracker sliders are usually positioned pretty close to where you would like them to be (10% to 15% error on average). This makes tracking faster ... and fun. This is the most convincing usage of « forecasts »: there is no way that Knomee could predict your future with the small amount of data that you track, but making Knomee « active » makes it faster to use ... and more fun ! Once you have enough data, it is actually amusing to see when Knomee gets it right and when it does not (usually, these are the most interesting self-tracking moments). The second use of this « smart » algorithm is to evaluate the relevance of more classical statistical observation. The scoring that Knomee reports about the influence of factors (tracker, time, location) is a combination of correlation and contribution to the AI insights.

 

(2) How to Grow a Unique Algorithm from your Data 

The emphasis in Knomee is on robustness much more than on precision. In the world of “small time series” (which is precisely why you get with bio-rhythms), high fidelity forecasting is an illusion and the common curse is “overfitting”: trying desperately to see some sense where there is none.

This forecasting algorithm is produced using program synthesis and reinforcement learning. Knomee has crafted an abstract description of meaningful patterns for biorhythm time series (a term algebra) and use randomization techniques to explore the wide space of possible variations. It then selects an evolutionary meta-search method to optimize the programs that better fit (reinforcement) according to their ability to explain the data. The search space includes the set of classical techniques such as k-neighbors or regression, but the evolutionary control protocol is geared at escaping the classical overfitting trap (after all, we never expect you to self-track a large amount of data).

We call the meta-algorithm that runs in your smartphone RIES for Randomized Incremental Evolutionary Search - it is a short-time series variation of techniques that were developed many years ago.  It is part of a method named EMLA (Evolutionary Machine Learning Agents); the « Incremental » specificity of the Knomee implementation is that it is optimized to fit the limited capacity of a smartphone (from a machine learning perspective).

 

(3) This Algorithm is Unique to You because You are Unique 

The RIES "algorithm factory" produces an algorithm that is truly unique because it is grown from your data. This algorithm is born on your phone and stays there. No-one will have access to the set of insights that is embedded into this algorithm. This approach is not meant for scaling or abstracting from multiple individuals.

The most interesting characteristic of EMLA is its ability to avoid false positives and let you know if your data has no relevant or statistically significant insights. This is especially critical for users because we get many of our quests wrong! We believe that we could improve some aspect of our well-being by changing our behavior ... and it simply does not work. As Mark Twain famously quoted « It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so. »

If you track “noise” (random data), Knomee will avoid overfitting and tell you that nothing much can be learned from your self-tracking data. It may does not sound like much, but it is a great feature of Knomee and something that distinguishes it from dubious so-called machine learning applications.

Posted by knomee on

Knomee is now a partner for quest tracking

Knomee is looking for partners to propose quests to our users. In other words, Knomee is a self-tracking customizable application that could be used by the following:

  • Coaches, who want to propose a self-tracking pattern to their students, from sports to fitness or mental well-being.
  • Healthcare professionals, who are looking for a tool to implement self-tracking studies.
  • Wearables device startups, to deliver more value around their connected objects. Most connected objects come with a specific mobile app or with HealthKit connectivity, but framing “quests” (multiple things to track as a whole) makes it much more interesting.

Why would such individuals or companies be interested with this proposal? Knomee is a unique qualitative tracker. Quantitative tracking through sensors, wearables and smartphone is much easier (automatic) but it is not enough for most quests. Qualitative means tracking with words instead of numbers. It requires customization (so that the words are uniquely fit to the individual) but mostly it requires ease of use. Qualitative tracking is much more difficult as illustrated by the poor fate of mood trackers.

Knomee aims to solve this challenge of “qualitative tracking”:

  • Efficiently : Knomee is organized around a “one screen operation” where everything is done with your thumb. You may track a full quest in less than 15 seconds.
  • In a fun way: Knomee anticipates your input through adaptive forecasting, making self-tracking a game. Knomee gives you illustrated as well as analytical feedback through mountains and weather metaphors.
  • Fully customizable: Knomee is a self-tracking factory.
  • A few trackers at a time : Knomee lets you track a unit that makes sense (a quest, not a simple tracker, where you get instant visual feedback in a global way).

Knomee offers this ability to our future partners for free. By defining your proposed quest, you can offer to your customers a free tracking app that is a best-in-class solution for qualitative self-tracking. You simply need to use Knomee to define your quest, and export it back to us as a JSON file. To get more details on how to proceed, contact us at knomyself@gmail.com

What is new in January release (1.5) ?

  • New onboarding: Onboarding for new Knomee users has been made much easier and simpler.
  • Time tracking: a new kind of tracker has been added to keep time measurements (in hour & minutes).
  • Quest library: Knomee offers a list of quests that may be used directly or customized (used as a template). This makes learning how to use and define quests easier. This open library is the platform for the partnerships regarding new quests.
  • The User Manual screen and the Kenscore screen have been separated, hence each one is much simpler, a request from our early users.

The partnership opportunity is open to anyone who would like to share a quest. If you have defined a quest that you think would be of interest to others, send it to yourself (this is done by pressing "edit" on the home screen, to access the “setup” screen that provides an export menu button) and then share it with us (through email). It will be added to the quest library next month. You decide if you want to be quoted as the quest source (your name) or if you prefer to be anonymous.

Posted by knomee on

Why in the world propose yet another self-tracker ?

Knomee is a self-tracker app for mood, health, sports, lifestyle … you track whatever you want.

  • Knomee is completely customizable. Knomee works for quantified trackers (weight, elapsed time, heart rate) and qualitative ones (mood, quality of food or sleep, how you feel). Knomee lets you use your own words and define your very own trackers.
  • HealthKit compatible for steps, heart rate, sleep and weight. You may import these values from your phone or connected devices automatically if you want to.

Tracking is not enough, Knomee helps you to define quests, a group of things that you want to track together. A quest may be used to improve your well-being (as defined by the main tracker) through some behaviour changes (as defined by other trackers called factors). You may simply want to understand the effect of these factors on your main tracker, without any idea of change. The quest represents a question to yourself: is there a link between these factors (what you smoke, how you sleep, what you eat …) and your main tracker (how you feel, sleep, how fast you run ….) ? We call this “self-tracking with sense”: you self-track to understand yourself better. You pick a “main” tracker and associate a few (1 to 3) “factor” trackers that you believe to be linked together. Knomee lets you:

  • Track a quest with one screen and one finger (much faster that tracking a set of things separately) with instant visual feedback,
  • Manage multiple quests – Quests come and go, some make sense and some don’t. Knomee helps you to find out quickly what works for you and what does not.

Seeing your data is not enough, Knomee has a built-in data scientist inside. This helps you understand yourself better through your quests.

  • Knomee colors what helps and what does not on your measure tracker screen. Green-colored trackers may have a positive influence on your goal, while red-colored trackers may play against your goal.
  • Knomee proposes “factor analysis” including time, day and location. This helps look at your self-tracking data and make sense of the curves.
  • Knomee gives you insights to help you understand yourself better. After a few weeks Knomee may send you notification from your built-in data scientist.

Self-tracking is quickly boring, so Knomee makes it fun !

  • Knomee uses an AI agent that forecasts what you are going to say next. It saves you time when it’s right … and it’s fun (and interesting because it usually is a special moment) when it’s wrong.
  • Knomee design is optimized for speed : open the app, self-track a couple of measures, and quit in 15 second
  • Knomee uses friendly mountains icons with weather to indicate where you stand with respect to your own targets.

Everything is built in the app and your data will not leave your phone. There are no back-ends, Knomee is not a service. It is a 21st century notebook with built-in smart, visual and fun analytics.

Posted by knomee on

Why does Knomee show 3 weeks of history on the home page ?

Knomee shows your data history on the home page, using a 21 days (3 weeks) window.

You may have noticed that the home page has three parts:

  • on the right, you see a mountain icon for each tracker that represents the qualitative status of this tracker
  • in the middle, you see the chart of what was tracked during the last three weeks
  • on the left, you have the sliders that you use to add  a new measure (one slider round button for each tracker)

We use a sliding window of three weeks because behavioral science tells us that this is the proper time horizon to see if you are making progress. You may access all of your data in the "chart view", that is, the screen that you get when swiping down (or clicking on the eye button).

Three weeks has shown to be a meaningful time horizon. There is enough data so that you can see the trend, and it is short enough to recollect what happened. Interestingly, 3 weeks is long enough to filter out non-lasting impulse or reactive changes. Something that happens over 21 days seems to be significant.

This does not mean that you will change your behaviour in 21 days ! Science has shown that it takes longer and that 21 days (3 weeks) is too short. However, 21 days is long enough so that what you see is meaningful (either improvement or decline), even if stability has not been reached yet. Using a shorter period of time (one or two weeks) would indeed be too short.
You will also find that when you look at 100 days of data, using the chart view, it is harder to make sense and to remember what happened.